Electronic discovery, commonly referred to as e-discovery or eDiscovery, refers to any process in which electronic data is sought, located, secured and searched with the intent of using it as evidence in a legal proceeding, an audit, a regulatory investigation, a forensics investigation or the like. E-discovery can be carried out offline on a particular computer or it can be accomplished in a network environment.
The nature of digital data makes it extremely well-suited for investigation. In particular, digital data can be electronically searched with ease, while paper documents must be scrutinized manually. Furthermore, it is difficult or impossible to completely destroy digital data, particularly if the data is stored in a network environment. This is because the data appears on multiple hard drives, and because digital files, even if deleted, generally can be undeleted. In fact, the only reliable means of destroying digital data is to physically destroy any and all hard drives where it is stored.
In the process of electronic discovery, data of all types can serve as evidence. This can include text, image, calendar event data, databases, spreadsheets, audio files, multimedia files, web sites and computer programs. Electronic mail (i.e., e-mail) can be an especially valuable source of evidence in civil or criminal litigation, because people are often less careful in these exchanges than in hard copy correspondence such as written memos or postal letters. Certain regulations and other business needs require email to be retained for years.
E-discovery is an evolving field that goes far beyond mere technology. It gives rise to multiple issues, many of which have yet to be resolved. For example, identifying data required to satisfy a given discovery request, locating the appropriate set of data that has been identified, and retrieving the data once it has been identified and located all pose problems in and of themselves. This is especially evident if the data that is being identified, located and retrieved comes from an evolving or disparate enterprise, such as a corporation that has experienced mergers, acquisitions, downsizing and the like. Mergers and acquisitions mean that the technology infrastructure across the enterprise may vary, at least in the interim. However, e-discovery must be able locate and retrieve data from these disparate technology infrastructure in a timely fashion, sometimes within days of when the merger/acquisition occurs.
In addition to identifying, locating and retrieving digital data, the most critical part of any electronic discovery is the preservation of data, which involves maintaining an original source copy and storing it for preservation purposes or furthering processing. This too becomes a daunting task for the enterprise system that encompasses a myriad of different technology infrastructures and the like. Therefore, a need exists to improve the identification, location, retrieval and preservation processes, especially in instances in which the enterprise system includes disparate technology infrastructures and the like.
As previously noted, e-discovery, as opposed as conventional discovery of printed materials, provides for the ability to filter or search the data so as to reduce the volume of data to only that which is relevant to the request. Such searching is typically accomplished by determining a specific date range for the request, providing key words relevant to the case and the like. Searches using conceptual concepts, heuristics, linguistics and other variants are also becoming common. Still though, improvements in the area of searching are greatly in need to further add efficiency to the overall e-discovery process.
Once data has been retrieved, preserved and, in some instances, searched the electronic data may be reviewed by the requesting entity, such as a law firm, securities commission or the like. While large requests are generally suited for online review, the manner in which the data is presented for review adds efficiency to the review process and ultimately drives the cost of the review process. Therefore, improvements in the manner in which data is presented for review are also desirable as a means of increasing efficiency and reducing costs.
Lastly, once the digital data has been reviewed, data identified as relevant may need to be produced in a tangible format for further analysis or legal evidentiary purposes. The produced documents must be properly identified and include necessary redactions and confidentiality markings.
Currently, most e-discovery processing has been conducted manually or, in instances in which automated processing has been conducted, manual actions have been required to initiate the next step in the process. For example, processes such as, data collection, barcoding of data, source-to-processing functionality, quality control checks, third-party network data transfer and data analysis platform loading have, in-part or in whole, required case analyst intervention in order to complete the process. Such manual processing is inefficient, in that, invariably, time is lost waiting for a case analyst or someone else tasked to perform a function to perform the requisite action.
Therefore, a need exists to develop an automated system for processing of data in an electronic discovery system. The desired system should minimize case analyst or other associate intervention, such that case analyst or other associate intervention is only required in the event that a process is unable to automatically continue. The desired process should assign tasks to services that are executed automatically and, based on completion of the tasks, look for the next decision point in the overall data processing flow and continue processing until an exception occurs in the process, which may require manual intervention. Such straight-through type processing significantly reduces the time necessary to process electronic discovery data and, significantly reduces the man-power requirements associated with a labor-intensive methodology.